Hi, Community!
I'm Sid, founder of Purna AI. We've been building a Molecular Intelligence Platform for the last few months, and now it's in research preview. It's a single workspace where molecular medicine teams can go from raw biology data to interpretation without juggling a dozen disconnected tools.
## The Problem
If you work in clinical genomics, rare disease research, computational biology, or similar fields, your workflow probably looks like this: export variants from one tool, look up annotations in another, cross-reference ClinVar, check gnomAD frequencies, read ACMG guidelines in a PDF, pull up a protein structure viewer separately, then paste everything into a report. Multiply that by hundreds of variants per case.
It's slow, error-prone, and most of the "analysis" time is actually spent on context-switching or copy-pasting existing scripts.
## What MIP Does
- *Singular Workspace for Biological Analysis* - Genetics, Epigenetics, Single Cell RNA, and more - *AI-powered pipelines* - Can write complex pipelines, execute on a secure compute instance, and give you results in natural language - *Variant analysis* with ACMG classification built in - *Integrated with 30+ clinical databases* - ClinVar, gnomAD, OMIM, UniProt, etc. - *Protein structure prediction with Chat* - Compare Wildtype vs Mutant Variations - *AI-assisted interpretation*, reclassification, and reporting - *Auditable Case Management* so nothing falls through the cracks
The AI layer is the key differentiator. We benchmarked it against 1,600 genomics queries from an Oxford dataset and hit 90%+ accuracy. But more importantly, it handles the kind of nuanced, multi-step reasoning that comes up in real casework, for example: "Is this VUS in a conserved domain?", "What's the functional impact given this patient's phenotype?", "Are there any recent publications reclassifying this variant?"
## The Backstory
I'm an engineer, not a biologist. We started building in the Preventive Healthcare (early diagnosis) space. Watching clinicians work with fragmented tools while making critical diagnostic decisions felt like a solvable problem. My co-founder Dr. Gitanjali (CMO) keeps us grounded in clinical reality.
## Where We Are
Early stage, two founders. We are now inviting scientists and biologists around the world to test more complex cases. We have already processed over 50 samples ourselves on the platform, and seeing PhD-grade results.
## What I'd Love From the Rainmatter Community
- If you work in *genomics, bioinformatics, drug discovery*, or similar fields, we'd love to give this to you and your team for early feedback. - If you've built *developer tools or "IDE-for-X" products*: what did you learn about adoption in specialized domains? - If you've done *B2B SaaS for life sciences*: any hard-won lessons on selling to labs and research institutions?
Happy to answer any questions about the tech, the biology, or the business.
*Check us out here:* purna.ai